Complete Stacked Denoising Auto-Encoders for Regression

Complete modified stacked denoising auto-encoder (CMSDAE) machines constitute a version of stacked auto-encoders in which a target estimate is included at the input, and are trained layer-by-layer by minimizing a convex combination of the errors corresponding to the input sample and the target. This...

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Bibliographic Details
Published in:	Neural processing letters Vol. 53; no. 1; pp. 787 - 797
Main Authors:	Fernández-García, María-Elena, Sancho-Gómez, José-Luis, Ros-Ros, Antonio, Figueiras-Vidal, Aníbal R.
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.02.2021 Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Coders Complex Systems Computational Intelligence Computer Science Concrete Datasets Experiments Noise reduction Regression Time series Variables Regression Complete auto-encoders Neural networks Denoising
ISSN:	1370-4621, 1573-773X
Online Access:	Get full text
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